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Decision irrationalities involving deadly risks

Author

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  • W. Kip Viscusi

    (Vanderbilt Law School)

  • Scott DeAngelis

    (Robinson, Bradshaw, & Hinson)

Abstract

This article provides an experimental analysis of two-armed bandit problems that have a different structure in which the first unsuccessful outcome leads to termination of the game. It differs from a conventional two-armed bandit problem in that there is no opportunity to alter behavior after an unsuccessful outcome. Introducing the risk of death into a sequential decision problem alters the structure of the problem. Even though play ends after an unsuccessful outcome, Bayesian learning after successful outcomes has a potential function in this class of two-armed bandit problems. Increasing uncertainty boosts the chance of long-term survival since ambiguous probabilities of survival are increased more after each successful outcome. In the independent choice experiments, a slim majority of participants displayed a preference for greater risk ambiguity. Particularly in the interdependent choice experiments, participants were overly deterred by ambiguity. For both independent and interdependent choices, there were several dimensions on which participants displayed within session rationality. However, participants failed to learn and improve their strategy over a series of rounds, which is consistent with evidence of bounded rationality in other challenging games.

Suggested Citation

  • W. Kip Viscusi & Scott DeAngelis, 2018. "Decision irrationalities involving deadly risks," Journal of Risk and Uncertainty, Springer, vol. 57(3), pages 225-252, December.
  • Handle: RePEc:kap:jrisku:v:57:y:2018:i:3:d:10.1007_s11166-018-9292-4
    DOI: 10.1007/s11166-018-9292-4
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    References listed on IDEAS

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    Cited by:

    1. W. Kip Viscusi, 2020. "Electronic cigarette risk beliefs and usage after the vaping illness outbreak," Journal of Risk and Uncertainty, Springer, vol. 60(3), pages 259-279, June.
    2. Carlos Alós-Ferrer & Alexander Jaudas & Alexander Ritschel, 2021. "Effortful Bayesian updating: A pupil-dilation study," Journal of Risk and Uncertainty, Springer, vol. 63(1), pages 81-102, August.

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